Data is the lifeblood of the Internet era and the foundation for Industry 4.0. Since
the mid-1990s, data has increasingly been created, shared, hosted, and stored online. As of 2021, there are over 4.7 billion unique Internet users with 8.3 billion connected devices and equipment. Both figures are expected to grow into 7.5 billion and 30 billion, respectively, by 2030.
In addition, with the ongoing digital industrial transformation, trillions of data points will be generated every day, not only from humans but also from the tens of billions of sensors, machines, and infrastructures deployed to provide more visibility on business and technology operation processes. These data points need to be refined, processed, analyzed, and used to make better decisions on the information
they carry.
Many organizations are aware of the importance of data and have set up various
tools to harvest insights from the data they own. As data volume grows, these
organizations resort to the automated data analytics process. Data Operations (DataOps) are a set of software tools, technical practices, and workflows that can churn out valuable insights from big data, including forecasts and predictions on customer behavior, operational efficiency, supply chain management, and much more. These insights can then be turned into feedback to optimize further and enhance the accuracy of the data analytics outputs.
Download the whitepaper to learn more.
